{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "results = np.load('coverage_results.npy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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FRDxCgS4i4hEKdBERj1Cgi4h4xIVzY1Fmak1XICLi13SGLiLiEQp0ERGPUKCL\niHiEAl1ExCMU6CIiHqFAFxHxCAW6iIhHKNBFRDziwrmxSC5aYW5nhV6/ydpUUiUi/k1n6CIiHqFA\nFxHxCAW6iIhHKNBFRDxCgS4i4hEKdBERj1Cgi4h4hAJdRMQjdGPRBSL84+Gltvkq9q/VUMmFpyI3\nJummJP/UavzSmi7hvO2efFuV70Nn6CIiHqFAFxHxCAW6iIhHKNBFRDyiQoHunOvvnPvGObfdOTe+\nsooSEZHzV+5Ad84FADOAAUAoMMw5F1pZhYmIyPmpyBl6D2C7me00s1PAfGBQ5ZQlIiLnqyKB3hzY\ne9bzjPxlIiJSAypyY5ErYpmd08i5kcDI/Kc5zrlvStluEHCwAnVVN7+p19G1LM38pt4yuJBqBdVb\n1S7oet2UCm3rmrI0qkigZwBXn/W8BZBZuJGZvQK8UtaNOufWm1n3CtRVrVRv1bmQagXVW9VUb+kq\nMuSyDmjvnGvtnLsEiAcWV05ZIiJyvsp9hm5muc65R4AVQAAw28y+rrTKRETkvFRoci4zWwYsq6Ra\nzijz8IyfUL1V50KqFVRvVVO9pXBm57yPKSIiFyDd+i8i4hE1FujOud3Oua+cc2nOufVFrI9xzh3J\nX5/mnJtQE3WeVc/lzrkFzrktzrl059z1hdY759z/5k+D8KVzrkzXENZQrX7Tt865jmfVkeacO+qc\n+12hNv7Ut2Wp12/6N7+e0c65r51zm5xz85xzdQut96f+La1Wf+vbR/Nr/brwz0H++urtWzOrkS9g\nNxBUwvoY4MOaqq+IeuYCD+Y/vgS4vND6gcBH5F2fHw187se1+lXfnlVXAPA9cI2/9m0Z6/Wb/iXv\nZr9dwKX5z98FHvDH/i1jrf7Ut2HAJqAeee9H/h1oX5N9qyGXMnDOXQb0BF4DMLNTZna4ULNBwF8t\nz2fA5c65ZtVcallr9Vd9gB1m9m2h5X7Rt0Uorl5/Ewhc6pwLJC98Ct8v4k/9W1qt/iQE+MzMjptZ\nLpAM3FWoTbX2bU0GugErnXMb8u8mLcr1zrkvnHMfOec6V2dxhbQBsoDXnXOpzrlXnXP1C7Xxl6kQ\nylIr+E/fni0emFfEcn/p28KKqxf8pH/NbB/wArAH+A44YmYrCzXzi/4tY63gJ31L3tl5T+dcY+dc\nPfLOxq8u1KZa+7YmA/1GM+tK3myNv3HO9Sy0fiN5f8pGAi8BH1R3gWcJBLoCM80sCvgBKDxdcJmm\nQqgGZanVn/oWgPyb0+4A/lbU6iKW1ejlWaXU6zf965y7gryzxNZAMFDfOXd/4WZFvLTa+7eMtfpN\n35pZOjAF+BhYDnwB5BZqVq2Fpu4bAAABoklEQVR9W2OBbmaZ+f8eABaSN3vj2euPmllO/uNlQG3n\nXFC1F5onA8gws8/zny+AcyZOKdNUCNWg1Fr9rG/PGABsNLP9Razzl749W7H1+ln/9gV2mVmWmZ0G\n3gduKNTGX/q31Fr9rG8xs9fMrKuZ9QT+BWwr1KRa+7ZGAt05V9851/DMY+BW8v58ObvNVc45l/+4\nB3m1Zld3rQBm9j2w1znXMX9RH2BzoWaLgeH572pHk/fn4nfVWSeUrVZ/6tuzDKP44Qu/6NtCiq3X\nz/p3DxDtnKuXX1MfIL1QG3/p31Jr9bO+xTl3Zf6/LYHBnPszUa19W6E7RSugKbAw//sSCLxtZsud\nc6MAzGwWcDfwsHMuF/gRiLf8t41ryH8Bb+X/qb0TGFGo3mXkjaFtB44DI2qqUEqv1a/6Nn/8MRZ4\n6Kxl/tq3ZanXb/rXzD53zi0gb6giF0gFXvHH/i1jrX7Tt/nec841Bk4DvzGzQzXZt7pTVETEI3TZ\nooiIRyjQRUQ8QoEuIuIRCnQREY9QoIuIeIQCXUTEIxToIiIeoUAXEfGI/w9lwlAUcDRKWwAAAABJ\nRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.hist(results[:, 1], label='dmlateiv: {}'.format(np.mean(results[:, 1])))\n",
    "plt.hist(results[:, 4], label='driv: {}'.format(np.mean(results[:, 4])), alpha=.2)\n",
    "plt.hist(np.mean(results[:, 0]))\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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TLjAwECkl0dHRRq87PSmOzLQUAi14+WNNAsfP4Pbt2+zZs0frUBQT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\n0UIp7hERLfQPatrGOE4kjLQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "from scipy.stats import norm\n",
    "\n",
    "(mu, sigma) = norm.fit(results[:, 1])\n",
    "sns.distplot(results[:, 1], fit=norm, kde=False, norm_hist=True, label='dmlateiv: {:.2f}, {:.2f}'.format(mu, sigma))\n",
    "\n",
    "(mu, sigma) = norm.fit(results[:, 4])\n",
    "sns.distplot(results[:, 4], fit=norm, kde=False, norm_hist=True, label='driv: {:.2f}, {:.2f}'.format(mu, sigma))\n",
    "plt.title(\"DMLATEIV vs DRIV: Truth={:.2f}\".format(np.mean(results[:, 0])))\n",
    "plt.legend()\n",
    "plt.savefig(\"cov_exp_1.pdf\", dpi=300, bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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liXbc7me4+mrYc89Ql+Kf/4R//UvJQKQB0uJwA5NsNFAXBzV7m3+V94LrFoSs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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import statsmodels.api as sm\n",
    "import scipy.stats as stats\n",
    "std = np.mean(results[:, 6] - results[:, 5])/4\n",
    "sm.qqplot((results[:, 4] - np.mean(results[:, 0]))/std, line='45')\n",
    "plt.savefig(\"cov_exp_2.pdf\", dpi=300, bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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uPNIAK1aEw2puuAE23jhk+JNOUv8hqTkhuPsr+QrC3T83s9HAkcCMOh4uETRm5ZCmhVJk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\nRK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import statsmodels.api as sm\n",
    "import scipy.stats as stats\n",
    "std = np.mean(results[:, 3] - results[:, 2])/4\n",
    "sm.qqplot((results[:, 1] - np.mean(results[:, 0]))/std, line='45')\n",
    "plt.savefig(\"cov_exp_3.pdf\", dpi=300, bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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YAL6T5JFlVTYBT51WD9cPx7Y+bdSxbdRxwYyPLX/Wa/dLJ9GHPqFwFLhkYP1iYHGMOgBU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\nQ0GS1Pw/Wnu67bJFLKcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(results[:, 3] - results[:, 2])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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A+qGu7HjbSJJeRH1u2ZAhZTVGm9mGyVZmTwcBPJfk0R5jW2prgKeWexAvghbm6RxXh1Ux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\nJDXmfwGwVVO3u5bWAAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(results[:, 6] - results[:, 5])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Coverage DMLATE: 0.260\n",
      "Coverage DRIV: 0.940\n"
     ]
    }
   ],
   "source": [
    "print(\"Coverage DMLATE: {:.3f}\".format(np.mean((results[:, 0] >= results[:, 2]) & (results[:, 0] <= results[:, 3]))))\n",
    "print(\"Coverage DRIV: {:.3f}\".format(np.mean((results[:, 0] >= results[:, 5]) & (results[:, 0] <= results[:, 6]))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
